ba-mod 5-modeling it systems v0.4
TRANSCRIPT
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Module 5
Software EstimationModeling IT Systems
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Topics in Estimation
Software Estimation
Size Estimation
Effort Estimation
Schedule Estimation
Agile Size Estimation
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Sources of Uncertainty
Will the customer want Feature X?
Will the customer want the cheap orexpensive version of Feature X?
If you implement the cheap versionof Feature X, will the customer later
want the expensive version after all? How will Feature X be designed?
What will be the quality level ofFeature X?
How long will it take to debug andcorrect the mistakes made in theimplementation of Feature X?
How long will it take to integrateFeature X with all the other features?
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Estimate Convergence Graph
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Estimation process overview
Estimate the size of the product (number oflines of code or function points) Use an algorithmic approach e.g. function
points, that estimates size from program features
Use size-estimation software
If you have worked on a previous project that issimilar you can estimate from that
Estimate the effort (person-months)
Estimate the schedule (calendar months)
A more general step (a meta-step) Provide estimates in ranges and periodically
refine the ranges to provide increasing precisionas the project progresses
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Size Estimation
Algorithmic approach such as function points, that estimates program
size from program features
Use size-estimation software that estimatesprogram size from your description of
program features screens, dialogs, files, database tables, etc.
If you have already worked on a similarproject and know its size Estimate each major piece of the new system as a
% of the size of a similar piece of the old system. Add up all the estimated sizes of the pieces
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Function-Point Estimation
This kind of size estimation is often used ina projects early stages
Based on counting
Inputs screens, forms, dialog boxes,
controls etc.Outputs screens, reports, graphs etc.
Inquiries input/output combinations
Logical internal files files controlled by
the programExternal interface files files controlled by
other programs
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Function-Point Multipliers
LowComplexit
y
x3
x 4
x 3
x 7
x 5
Medium
Complexity
x 4
x 5
x 4
x 10
x 7
High
Complexity
x 6
x 7
x 6
x 15
x 10
ProgramCharacteristics
Number of inputsNumber of outputs
Inquiries
Logical internalfiles
Logical interfacefiles
Function Points
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Estimation Tips
Avoid off-the-cuff estimates
Allow time for the estimate, and plan it
Use data from previous projects
Use developer-based estimates
Estimate by walkthrough Estimate by categories e.g. easy, medium,
hard
Estimate at a low level of detail
Dont omit common tasks
Use software estimation tools Use several different estimation techniques,
and compare the results
Change estimation practices as the project
progresses
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Estimate Presentation Styles
Plus-or-minus qualifiers
Ranges
Risk quantification
Cases Best case, planned case, current case, worstcase
Coarse dates and time periods
Confidence factors E.g. delivery date April 1, probability of
delivering on time 5%
May 1, probability of delivering on time 50%
June 1, probability of delivering on time 95%
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Effort Estimation
Once you have the sizeestimate you derive theeffortestimate Use estimation software to
create an effort estimate
directly from the sizeestimate Use your organizations
historical data to determinehow much effort previousprojects of the estimated
size took Use an algorithmic
approach to convert a lines-of-code estimate into aneffort estimate
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Schedule Estimation
The third step (the first is estimating sizeand the second is estimating effort) inestimating a software project is tocompute the schedule estimate
Software Schedule Equation Schedule in months = 3.0 * Person-months1/3
Once youve estimated that it will take 65man-months to build the project, theequation says that the optimal schedule is12 months (3.0 * 65 1/3 )
If you end up with an optimal schedule of12 months to do a project that requires65-man-months you will need 5-6 teammembers (65 man months divided by 12months)
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Agile Size Estimates
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Story Points The huge-ness of a
task
Relative deduction,factors are Complexity
Scope
Relative values arewhat is important: A login screen is a 2
A search feature is an 8
Points are unit-less
Scale of 1-10 ideally
Average task 5
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Ideal Days Time taken if
its all you worked on you had no
interruptions and everything you
need is available
The ideal time of afootball game is 90minutes Two 45-minute halves
The elapsed time ismuch longer (3hours?)
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Comparing Approaches
Story points help drive cross-functional behavior Story point estimates do not decay
Story points are a pure measure of size
Estimating in story points is typically faster
My ideal days cannot be added to your ideal days
Ideal days are easier to explain outside the team Ideal days are easier to estimate at first
Ideal days can force companies to confront timewasting activities
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How huge are these? Read a high-level, 10 page overview of agile
software development in a business magazine
Read a densely written 5 page research paperabout agile software development in aacademic journal
Write the product backlog for a simpleeCommerce site that sells only beer
Recruit, interview, and hire a new member foryour team
Create a 60 minute presentation about agile
estimating and planning for your co-workers Read a 150-page book on agile software
development
Write a 8-page summary of this session for yourboss
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Agile Estimation Methods
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Triangulation Comparing a user
story to others This story is like that
story, so its estimate iswhat that storysestimate was.
Dont use a singlegold standard
Triangulate instead Confirm estimates by
comparing the story tomultiple other stories.
Group like-sized storieson table or whiteboard
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Planning Poker An iterative approach to
estimating Steps
Each estimator is given adeck of cards, each card hasa valid estimate written on it
Product owner reads a story
and its discussed briefly Each estimator selects a card
thats his or her estimate
Cards are turned over so allcan see them
Discuss differences
(especially outliners) Re-estimate until estimatesconverge
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IT Systems Modeling
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Statement on IT System Modeling
A picture is worth thousand words
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IT System Modeling
Modeling Functions
Use Case Modeling
Structured SystemAnalysis and Design
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IT System Modeling
Use Case Modeling
Actor User Role
Another system
Time
Use Case
System Boundary
Association Include
Extend Pls. draw fig 10.2
on P.162
Set up Project
Assign Resources
Track Progress
Print ProgressReport
Provide InvoiceData
Print PersonalSchedule
SummarizeProjects
IdentifyProjects
ProjectManager
Programm
Manager
Team Member
Financesystem
Project ControlSystem
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IT System Modeling
Modeling Data
Data attributes that theorganization (system)needs to maintain
Grouping of data
attributes (Entities) Relationships between
the entities
Entities can be
Physical Conceptual
Entity Type Vs. EntityOccurrence
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IT System Modeling
Entity Relations
One to One May not require additional
entity
One to Many Office to Employees
Mandatory
Optional
Many to Many Books and Publishers
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IT System Modeling
Object Modeling
Objects Items for which system
maintains data
Class Object Type
Attributes
Methods
Optional
Inheritance and
generalization
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Case Study on DataModeling
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Information Resource
Management
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IT System Modeling
Data Modeling
Also known as DataManagement
Data vs. Context
Data context is also
known as Meta Data Data management is
associated withmanaging raw data as
well as meta data
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Effect of Poor Data Management
People maintain and collect data that is notneeded any more;
The organisation has historic information that isno longer used;
The organisation holds a lot of data that isinaccessible to potential users;
Information is disseminated to more peoplethan it should be;
The organisation uses inefficient and out-of-date methods to collect, analyze, store andretrieve the data;
The organisation fails to collect data that itneeds.
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Challenges of Data QualityManagement
Lack of proper validation
Multiple non-integrateddata storage
Incomplete data
Proliferation of local PCs
Not considering non-electronic forms of data
Non-structured data suchas images, audio and video
No central agency for datamanagement
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Valuing and Classifying Data
Valuing data by availability
Valuing lost data
Data life cycle
Classifying data Operational ortransactional data
Tactical data (MIS, BI)
Strategic data
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Data Warehousing
Primarily used for what-if analysis
Contains historical data
Data de-normalized for
quicker data analysis
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End of Module
Any Questions?
Any Suggestions forImprovement?
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